基于gpu的快速遗传规划与人工发育系统

Simon Harding, W. Banzhaf
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引用次数: 68

摘要

在本文中,我们演示了使用图形处理单元(GPU)来加速进化计算应用程序,特别是遗传编程方法。我们表明,与典型的CPU实现相比,有可能将速度提高数百倍,将这些应用程序的GPU处理推向HPC领域。这种性能的提高也延伸到人工开发系统,其中进化的程序用于构建蜂窝系统。证明了该方法对基于元胞自动机的人工发育系统进行有效评估的可行性。
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Fast Genetic Programming and Artificial Developmental Systems on GPUs
In this paper we demonstrate the use of the graphics processing unit (GPU) to accelerate evolutionary computation applications, in particular genetic programming approaches. We show that it is possible to get speed increases of several hundred times over a typical CPU implementation, catapulting GPU processing for these applications into the realm of HPC This increase in performance also extends to artificial developmental systems, where evolved programs are used to construct cellular systems. Feasibility of this approach to efficiently evaluate artificial developmental systems based on cellular automata is demonstrated.
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